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Applied Statistics Remote Jobs in California (NOW HIRING)

Walmart

Staff, Data Scientist (Pricing)

Sunnyvale, CA · On-site +1

... remote and hybrid options are not available. About the Role: TheWalmart Global Tech Applied AI Data ... experimentation, and statistics to solve complex pricing and retail challenges. We develop ...

Weave

Senior AI Engineer

San Francisco, CA · On-site +1

$175K - $215K/yr

Reporting to the Head of Applied AI, your primary focus will be building the LLM-facing components ... Scientific or quantitative background in machine learning, statistics, computer science, biology ...

Spokeo

Principal Product Manager, Data Products

Pasadena, CA · On-site +1

$171K - $207K/yr

A Bachelor's degree in Computer Science, Information Systems, Analytics, Statistics, Applied Math ... As a remote-first company, we are able to hire team members residing in the following US states: AZ ...

Miami University

Visiting Faculty

Benicia, CA · On-site +1

... applied professional experience in a marketing-related field, including but not limited to product ... Remote work is not a right, it is a work arrangement that can be modified or revoked by Miami ...

6sense

Sr. Data Scientist

San Francisco, CA · Remote

$162K - $238K/yr

Strong foundation in Machine Learning, Statistics, and Applied Data Science. * Experience with ... remote Notice of Collection and Use of Personal Information for California Residents: California ...

AbbVie

Machine Learning Engineer

San Diego, CA · On-site +1

$109K/yr

Completed BS, MS, or PhD in Computer Science, Mathematics, Statistics, Data Science,Engineering ... Ability to work effectively in a remote environment using collaboration tools Preferred Experience ...

AbbVie

Machine Learning Engineer

San Diego, CA · On-site +1

Completed BS, MS, or PhD in Computer Science, Mathematics, Statistics, Data Science,Engineering ... Ability to work effectively in a remote environment using collaboration tools Preferred Experience ...

Workato

Staff AI Engineer

Palo Alto, CA · On-site +1

Quartz ranked us the #1 best company for remote workers Responsibilities As we work towards ... Collaborate with product and applied research teams to translate user needs into data-informed ...

Prosper

Credit Risk Analyst

San Francisco, CA · On-site +1

$122K - $140K/yr

We are looking for team members that share our passion for applied analysis and who would be ... Bachelors degree in Business, Statistics, Mathematics, Computer Science, Engineering or Economics ...

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All JobsApplied Statistics JobsApplied Statistics Remote JobsApplied Statistics Remote Jobs in California

Applied Statistics Remote information

What is an applied statistics remote job?

An Applied Statistics Remote job involves using statistical methods and data analysis techniques to solve real-world problems, all while working from a remote location. Professionals in this field collect, analyze, and interpret data to provide insights for decision-making across various industries such as healthcare, finance, and technology. Remote applied statisticians often collaborate virtually with teams, utilize statistical software, and communicate findings through reports or presentations. This role requires strong analytical skills, proficiency in statistical tools, and the ability to work independently.

What are the key skills and qualifications needed to thrive as an applied statistics professional in a remote role?

To thrive as an Applied Statistics professional working remotely, you need a solid background in statistical theory, data analysis, and a degree in statistics, mathematics, or a related field. Proficiency with statistical software such as R, Python, SAS, or SPSS, and familiarity with data visualization tools are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills are essential for interpreting data and collaborating virtually. These skills ensure accurate analyses, clear insights, and successful teamwork, which are crucial for delivering impactful statistical solutions in a remote environment.

What is the difference between Applied Statistics Remote vs Data Analyst?

AspectApplied Statistics RemoteData Analyst
Required CredentialsBachelor's or Master's in Statistics, Mathematics, or related fieldBachelor's in Statistics, Data Science, or related field
Work EnvironmentRemote, often project-based or contract rolesRemote or on-site, typically in corporate or tech settings
Industry UsageResearch, academia, consulting, tech companiesBusiness, finance, marketing, tech companies
Common Search/ComparisonApplied Statistics RemoteData Analyst

Applied Statistics Remote and Data Analyst roles share similar educational backgrounds and often work in remote environments. However, Applied Statistics Remote roles tend to focus more on statistical modeling and research, while Data Analysts often handle data visualization and reporting for business insights. Both roles are in high demand across various industries, with Applied Statistics Remote positions leaning more toward research and academic projects.

How does working remotely in an applied statistics role influence collaboration and project management with cross-functional teams?

In a remote applied statistics position, collaboration often relies on digital tools such as video conferencing, shared code repositories, and project management platforms. Statisticians frequently work with data scientists, engineers, and business stakeholders, making clear communication and documentation essential for successful project outcomes. Regular virtual meetings and asynchronous updates help align team objectives and ensure data-driven insights are integrated effectively. While remote work offers flexibility, it also requires proactive engagement to stay connected and maintain productivity within a distributed team environment.

Is applied statistics a good career?

Applied statistics is a strong career choice for those interested in data analysis, modeling, and decision-making, often requiring skills in programming languages like R or Python. It offers opportunities across various industries such as healthcare, finance, and technology, with competitive salaries and demand for professionals with statistical expertise. Continuous learning and certification can enhance job prospects in this field.

Where can I work with a degree in applied statistics?

With a degree in applied statistics, you can work in various industries such as healthcare, finance, marketing, and technology, often as a data analyst, statistician, or data scientist. These roles typically require skills in statistical software, programming languages like R or Python, and data visualization tools. Many positions are available in both remote and on-site environments across multiple sectors.
What are the most commonly searched types of Applied Statistics jobs in California? The most popular types of Applied Statistics jobs in California are:
What are popular job titles related to Applied Statistics Remote jobs in California? For Applied Statistics Remote jobs in California, the most frequently searched job titles are:
What job categories do people searching Applied Statistics Remote jobs in California look for? The top searched job categories for Applied Statistics Remote jobs in California are:
What cities in California are hiring for Applied Statistics Remote jobs? Cities in California with the most Applied Statistics Remote job openings:
Applied Statistics Remote jobs near you

Senior Principal Machine Learning Engineer - Optimization

PubMatic

Redwood City, CA • On-site, Remote

$153K - $211K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 17 days ago

Job description

Role: Hybrid in Redwood City, CA. (Will consider Remote for the right candidate)
Must have: Experience building large-scale prediction or optimization systems
PubMatic is the leading AI-powered ad tech company delivering measurable advertising performance through an intelligent, unified platform that connects buyers, publishers, data partners, and commerce media across CTV, mobile app, and omnichannel environments.
About the Role:
We are looking for a Senior Principal Machine Learning Engineer to help build the next generation of performance optimization capabilities for PubMatic's Activate platform.
This role is focused on applying machine learning, prediction, ranking, calibration, experimentation, and optimization techniques to improve campaign outcomes across performance advertising goals such as CTR, VCR, CPC, CPA, and ROAS. The ideal candidate has strong ML fundamentals and experience building large-scale production models or optimization systems.
What You'll Do:
  • Build and improve machine learning models for campaign optimization, prediction, ranking, bidding, forecasting, and calibration.
  • Develop models and algorithms that improve advertiser outcomes while balancing spend delivery, cost efficiency, campaign goals, marketplace dynamics, and system constraints.
  • Work on large-scale ML systems using signals from auctions, impressions, clicks, video events, conversions, users, context, inventory, campaigns, and marketplace feedback.
  • Design and improve CTR, CVR, VCR, CPA, ROAS, app-install, user-value, and campaign-performance models.
  • Develop bidding, pacing-aware optimization, ranking, exploration, and value-estimation approaches for performance advertising.
  • Improve model calibration, online/offline evaluation, experimentation, observability, and production feedback loops.
  • Reason through sparse conversions, delayed feedback, biased logs, cold-start campaigns, attribution noise, and online/offline metric mismatch.
  • Partner with performance advertising signal engineers to define model-ready features, labels, attribution windows, negative examples, training datasets, and online serving requirements.
  • Partner with engineering, product, analytics, and platform teams to translate model outputs into real-time decisioning systems.
  • Help evolve Activate from a media buying execution platform into a performance optimization platform.
  • Provide technical leadership and mentorship to engineers and applied scientists working on performance optimization problems.
  • 10+ years of experience building production machine learning, ranking, recommendation, prediction, optimization, ads, marketplace, bidding, or pricing systems.
  • Strong understanding of supervised learning, ranking, calibration, causal thinking, experimentation, statistical evaluation, and model monitoring.
  • Experience building large-scale prediction or optimization systems in production.
  • Experience with CTR/CVR prediction, conversion modeling, bid optimization, value modeling, forecasting, calibration, or performance optimization.
  • Strong ability to reason about model quality, business impact, system constraints, production tradeoffs, and online performance.
  • Experience working with large-scale data and distributed ML workflows.
  • Strong engineering skills in Python, Java, SQL, Spark, TensorFlow, PyTorch, XGBoost, or similar technologies.
  • Ability to provide technical leadership across ambiguous, high-impact optimization problems.
  • BS, MS, or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a related technical field.

Preferred Experience:
    • Experience in ads, search, recommendations, marketplaces, e-commerce, fintech, pricing, bidding, or real-time optimization systems.
    • Experience with performance advertising goals such as CTR, VCR, CPC, CPA, ROAS, app install, retargeting, or user-value optimization.
    • Familiarity with real-time bidding, programmatic advertising, ad serving, attribution, pacing, identity, incrementality, or performance advertising.
    • Experience with exploration/exploitation, counterfactual evaluation, uplift modeling, delayed-feedback modeling, or learning under biased logs.
    • Experience with model calibration, model observability, A/B testing, online experimentation, incrementality testing, or lift measurement.
    • Experience working cross-functionally with product, engineering, analytics, and business stakeholders.

We'd love for you to have:
  • 10+ years of experience building production machine learning, ranking, recommendation, prediction, optimization, ads, marketplace, bidding, or pricing systems.
  • Strong understanding of supervised learning, ranking, calibration, causal thinking, experimentation, statistical evaluation, and model monitoring.
  • Experience building large-scale prediction or optimization systems in production.
  • Experience with CTR/CVR prediction, conversion modeling, bid optimization, value modeling, forecasting, calibration, or performance optimization.
  • Strong ability to reason about model quality, business impact, system constraints, production tradeoffs, and online performance.
  • Experience working with large-scale data and distributed ML workflows.
  • Strong engineering skills in Python, Java, SQL, Spark, TensorFlow, PyTorch, XGBoost, or similar technologies.
  • Ability to provide technical leadership across ambiguous, high-impact optimization problems.
  • BS, MS, or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a related technical field.

Additional Information
Return to Office: PubMatic employees throughout the globe have returned to our offices via a hybrid work schedule (3 days "in office" and 2 days "working remotely") that is intended to maximize collaboration, innovation, and productivity among teams and across functions.
Benefits: Our benefits package includes the best of what leading organizations provide such as, paid leave programs, paid holidays, healthcare, dental and vision insurance, disability and life insurance, commuter benefits, physical and financial wellness programs, unlimited DTO in the US (that we actually require you to use!), reimbursement for mobile and fully stocked pantries plus in-office catered lunches 5 days per week.
Diversity and Inclusion: PubMatic is proud to be an equal opportunity employer; we don't just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status
About PubMatic
PubMatic is one of the world's leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.
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Compensation Disclosure
In accordance with applicable law, the below salary range provided is PubMatic's reasonable estimate of the total compensation for this role. New hires and current team members are typically compensated toward the middle of our pay range. The actual amount may vary, based on non-discriminatory factors such as location, experience, knowledge, skills and abilities. In addition to salary PubMatic also offers a bonus, restricted stock units, and a competitive benefits package.
Total Compensation Range
$260,000-$330,000 USD

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